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revised data types

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Andreas Gammelgaard Damsbo 2025-04-22 09:58:34 +02:00
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5 changed files with 84 additions and 38 deletions
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36
R/data_plots.R
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@ -408,7 +408,7 @@ all_but <- function(data, ...) {
#'
#' @examples
#' default_parsing(mtcars) |> subset_types("ordinal")
#' default_parsing(mtcars) |> subset_types(c("dichotomous", "ordinal", "categorical"))
#' default_parsing(mtcars) |> subset_types(c("dichotomous", "categorical"))
#' #' default_parsing(mtcars) |> subset_types("factor",class)
subset_types <- function(data, types, type.fun = data_type) {
data[sapply(data, type.fun) %in% types]
@ -443,58 +443,58 @@ supported_plots <- function() {
fun = "plot_hbars",
descr = "Stacked horizontal bars",
note = "A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars",
primary.type = c("dichotomous", "ordinal", "categorical"),
secondary.type = c("dichotomous", "ordinal", "categorical"),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "ordinal", "categorical"),
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_violin = list(
fun = "plot_violin",
descr = "Violin plot",
note = "A modern alternative to the classic boxplot to visualise data distribution",
primary.type = c("datatime", "continuous", "dichotomous", "ordinal", "categorical"),
secondary.type = c("dichotomous", "ordinal", "categorical"),
primary.type = c("datatime", "continuous", "dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
secondary.extra = "none",
tertiary.type = c("dichotomous", "ordinal", "categorical")
tertiary.type = c("dichotomous", "categorical")
),
# plot_ridge = list(
# descr = "Ridge plot",
# note = "An alternative option to visualise data distribution",
# primary.type = "continuous",
# secondary.type = c("dichotomous", "ordinal" ,"categorical"),
# tertiary.type = c("dichotomous", "ordinal" ,"categorical"),
# secondary.type = c("dichotomous" ,"categorical"),
# tertiary.type = c("dichotomous" ,"categorical"),
# secondary.extra = NULL
# ),
plot_sankey = list(
fun = "plot_sankey",
descr = "Sankey plot",
note = "A way of visualising change between groups",
primary.type = c("dichotomous", "ordinal", "categorical"),
secondary.type = c("dichotomous", "ordinal", "categorical"),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
secondary.extra = NULL,
tertiary.type = c("dichotomous", "ordinal", "categorical")
tertiary.type = c("dichotomous", "categorical")
),
plot_scatter = list(
fun = "plot_scatter",
descr = "Scatter plot",
note = "A classic way of showing the association between to variables",
primary.type = c("datatime", "continuous"),
secondary.type = c("datatime", "continuous", "ordinal", "categorical"),
secondary.type = c("datatime", "continuous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "ordinal", "categorical"),
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
),
plot_box = list(
fun = "plot_box",
descr = "Box plot",
note = "A classic way to plot data distribution by groups",
primary.type = c("datatime", "continuous", "dichotomous", "ordinal", "categorical"),
secondary.type = c("dichotomous", "ordinal", "categorical"),
primary.type = c("datatime", "continuous", "dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "ordinal", "categorical"),
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_euler = list(
@ -505,7 +505,7 @@ supported_plots <- function() {
secondary.type = "dichotomous",
secondary.multi = TRUE,
secondary.max = 4,
tertiary.type = c("dichotomous", "ordinal", "categorical"),
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
)
)